Sentinel AI

Autonomous security monitoring for distributed infrastructure — post-quantum encrypted, Byzantine fault-tolerant.

v2.1.0 NIST FIPS 203/204 247 reviews · 4.8★

Overview

Sentinel AI is an autonomous security monitoring agent designed for distributed infrastructure operators. Unlike traditional SIEM tools that require human triage, Sentinel uses Byzantine fault-tolerant consensus to validate threat signals across 7 geographically distributed sensor nodes before issuing an alert.

The core innovation is the threat validation pipeline: every security event must be independently confirmed by at least 5 of 7 sensors before it triggers a response. This eliminates false positives caused by single-node anomalies while maintaining sub-500ms detection latency for genuine threats.

Sentinel's telemetry is encrypted end-to-end using ML-KEM-768 (NIST FIPS 203), ensuring that intercepted network traffic reveals nothing about your infrastructure's security posture. Audit logs are signed with ML-DSA-87 (NIST FIPS 204) and anchored on the Lattice blockchain, providing tamper-evident proof of every detection event.

Key Features

Byzantine Fault-Tolerant Threat Validation

Traditional security tools produce alerts based on single-sensor readings, leading to alert fatigue from false positives. Sentinel's 5-of-7 consensus model means a threat is only flagged when independent sensors agree — eliminating 94% of false positives in our benchmark testing.

Post-Quantum Encrypted Telemetry

All sensor data, alerts, and audit trails use ML-KEM-768 for key encapsulation and AES-256-GCM for data encryption. Your security telemetry remains private even against adversaries with access to quantum computers. Sentinel was among the first security products to achieve NIST ACVTS validation for both ML-KEM-768 and ML-DSA-87.

Zero-Trust Agent Architecture

Sentinel agents authenticate via hardware-bound NFT identities. Each sensor node holds a unique ML-DSA-87 keypair anchored to its physical hardware. Compromising a sensor's credentials requires physical access to the device — network-based credential theft is architecturally prevented.

Architecture

Sentinel AI architecture diagram showing 7 distributed sensor nodes feeding into a Byzantine consensus coordinator, which validates threat signals before routing to the alert management system and encrypted audit log
Sentinel's consensus architecture: 7 independent sensor nodes, each running ML-KEM-768 encrypted telemetry channels. Threat signals require 5-of-7 agreement before escalation. The coordinator logs every consensus round to the Lattice blockchain via ML-DSA-87 signed receipts.
SENTINEL AI — CONSENSUS ARCHITECTURE [Sensor-01] ──┐ [Sensor-02] ──┤ [Sensor-03] ──┼──→ [BFT Coordinator] ──→ [Alert Manager] [Sensor-04] ──┤ 5/7 votes │ [Sensor-05] ──┤ ↓ [Sensor-06] ──┤ [Audit Chain] [Sensor-07] ──┘ ML-DSA-87 signed Latency: <500ms consensus finality False positive rate: <0.3% (industry avg: 23%) Uptime SLA: 99.95%

Technical Specifications

Specification Value Notes
Consensus protocolByzantine fault-tolerant (5-of-7)Tolerates 2 compromised nodes
Detection latencyp50: 180ms, p99: 470msEnd-to-end, consensus included
Key encapsulationML-KEM-768 (NIST FIPS 203)ACVTS validated April 2026
Digital signaturesML-DSA-87 (NIST FIPS 204)ACVTS validated April 2026
Symmetric encryptionAES-256-GCMNIST approved
Sensor nodes7 (minimum), 21 (recommended)Geographic distribution required
False positive rate<0.3%At default sensitivity
DeploymentDocker, bare metal, KubernetesARM64 and x86-64
Storage~2GB/month per nodeCompressed, encrypted telemetry
Memory512MB minimum per sensor1GB recommended

Quick Start

Installation

# Install Sentinel agent pip install sentinel-ai # Initialize with your Lattice identity sentinel init --lattice-identity your.lattice # Start the sensor daemon sentinel start --consensus-nodes 7 --region us-east

Python SDK — Threat Detection Integration

from sentinel_ai import SentinelClient, ThreatLevel # Connect to your Sentinel deployment client = SentinelClient( identity="your.lattice", consensus_threshold=5, # 5-of-7 required encryption="ML-KEM-768" ) # Subscribe to validated threat events async def handle_threat(event): if event.threat_level >= ThreatLevel.HIGH: await client.quarantine(event.source_node) await client.alert( severity=event.threat_level, evidence=event.consensus_receipt # blockchain proof ) client.on_threat(handle_threat) await client.start()

REST API

# Query current threat status curl -X GET https://api.sentinel-ai.io/v1/status -H "Authorization: Bearer {your_ml_dsa87_token}" # Response { "status": "operational", "active_sensors": 7, "consensus_health": "5/7 online", "threats_24h": 3, "false_positives_24h": 0, "last_consensus_ms": 247 }

Pricing

Feature Starter
$0/mo
Pro
$49/mo
Enterprise
$299/mo
Sensor nodes37Unlimited
Consensus threshold2-of-35-of-7Custom
Alert latency<2s<500ms<200ms
Audit chain7 days1 yearUnlimited
PQC encryption
ML-DSA-87 signing
HIPAA/SOC2
Custom rules50Unlimited
API accessRead onlyFullFull + webhooks
SLA99.9%99.95%
SupportCommunityEmail24/7 dedicated

Frequently Asked Questions

How does Byzantine consensus eliminate false positives?

Traditional IDS/IPS systems trigger on single-sensor anomalies. Sentinel requires independent confirmation from 5 of 7 geographically distributed sensors before flagging a threat. A false positive would need to simultaneously fool 5 independent sensors — statistically near-impossible. In our 6-month production benchmark, Sentinel logged 0 false positives at the 5-of-7 threshold while maintaining sub-500ms detection latency.

Why post-quantum cryptography for security telemetry?

Security telemetry is high-value target data. An adversary with a quantum computer could retroactively decrypt intercepted telemetry streams captured today — a "harvest now, decrypt later" attack. Using ML-KEM-768 (NIST FIPS 203) means your telemetry remains private even against future quantum adversaries. NIST finalized ML-KEM in August 2024. Federal agencies must migrate to PQC by 2030. Sentinel is ahead of that curve.

What happens if more than 2 sensor nodes go offline?

Sentinel enters a degraded-but-safe mode. With fewer than 5 active sensors, the consensus threshold cannot be met. Sentinel will log a warning, escalate to a backup alert channel, and continue collecting telemetry. It will not issue consensus-validated alerts until 5+ sensors are restored. This prevents both false positives (from operating below threshold) and silent failures (no alerting without notification).

Can I integrate Sentinel with my existing SIEM?

Yes. Sentinel exposes a standard STIX/TAXII feed for SIEM integration and a webhook system for real-time alert forwarding. Pre-built integrations exist for Splunk, Elastic Security, Microsoft Sentinel, and CrowdStrike. The REST API supports custom integrations. Enterprise tier includes dedicated integration support.

How is Sentinel different from CrowdStrike or SentinelOne?

CrowdStrike and SentinelOne are excellent endpoint detection tools. Sentinel AI focuses on infrastructure-level threat detection with cryptographic proof of every detection event. The key differences: (1) Byzantine consensus instead of single-agent detection, (2) post-quantum encrypted telemetry, (3) immutable audit chain on the Lattice blockchain, (4) hardware-bound sensor identity (credential theft is physically impossible). Sentinel complements rather than replaces endpoint tools.

User Reviews

★★★★★
Eliminated our alert fatigue overnight

We went from 300+ alerts/day with our previous tool to 12 actual threats/day with Sentinel. The 5-of-7 consensus is the real deal — if Sentinel fires, it's real. Our SOC team went from overwhelmed to actually investigating real threats.

— Marcus T., Infrastructure Security Lead, fintech company · March 2026
★★★★★
The only tool I've seen pass NIST ACVTS validation

We required PQC validation as part of our federal contractor compliance. Sentinel was the only commercial security monitoring tool that could show us actual NIST ACVTS test results for both ML-KEM-768 and ML-DSA-87. Implementation was straightforward and the audit chain on Lattice gives us non-repudiable evidence for every security event.

— Sarah K., CISO, defense contractor · February 2026
★★★★☆
Solid product, steep learning curve

The consensus architecture takes time to understand and tune. Documentation is good but assumes familiarity with BFT protocols. Once configured correctly, it's the most reliable detection system I've used in 15 years. The blockchain audit trail is genuinely useful for incident reconstruction. Wish the dashboard was more intuitive.

— DevOps Engineer, cloud infrastructure company · January 2026

Changelog

v2.1.0 — April 2026

v2.0.0 — February 2026